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Mahaffey K, Li J, Chang T, Sarraju A, Agarwal R, Charytan D, Greene T, Heerspink H, Levin A, Neal B, Pollock C, Yavin Y, Jardine M, Perkovic V, Cannon C. Independent predictors of heart failure in patients with type 2 diabetes and chronic kidney disease: modeling from the CREDENCE trial. Eur Heart J 2020. [DOI: 10.1093/ehjci/ehaa946.1175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background
SGLT2 inhibitors have been shown to reduce hospitalization for heart failure (HHF). We sought to determine independent baseline predictors for HHF specifically in a population with type 2 diabetes and chronic kidney disease (CKD).
Methods
CREDENCE randomized 4401 participants with type 2 diabetes and CKD to canagliflozin 100 mg versus placebo. We evaluated the baseline clinical and demographic factors using multivariate regression modeling to identify the independent predictors of HHF.
Results
Overall, 230 participants (89 canagliflozin; 141 placebo) had at least 1 HHF event. Canagliflozin reduced the incidence of HHF compared with placebo (4.0% vs 6.4%; HR 0.61; 95% CI 0.47–0.80). Participants with HHF events postrandomization were older (65.8 vs 62.9 y), and had a longer duration of diabetes (17.4 vs 15.7 y), higher prevalence of prior HF (30.4% vs 14.0%), higher urinary albumin:creatinine ratio (1347 vs 904 mg/g), lower estimated glomerular filtration rate (51.5 vs 56.4 mL/min/1.73m2), and higher prevalence of prior cardiovascular disease (65.7% vs 49.6%) compared to those without HHF. Independent predictors of HHF are shown in the Table.
Conclusions
HHF is common in patients with type 2 diabetes and CKD. Canagliflozin reduces HHF by 39% compared with placebo. Higher urinary albumin:creatinine ratio was the most potent predictor of HHF and should be part of patient risk assessment.
Funding Acknowledgement
Type of funding source: Private company. Main funding source(s): Janssen Research & Development, LLC
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Affiliation(s)
- K.W Mahaffey
- Stanford Center for Clinical Research, Dept of Medicine, Stanford University School of Medicine, Stanford, CA, United States of America
| | - J Li
- The George Institute for Global Health, UNSW Sydney, Sydney, Australia
| | - T.I Chang
- Stanford Center for Clinical Research, Dept of Medicine, Stanford University School of Medicine, Stanford, CA, United States of America
| | - A Sarraju
- Stanford Center for Clinical Research, Dept of Medicine, Stanford University School of Medicine, Stanford, CA, United States of America
| | - R Agarwal
- Indiana University School of Medicine and VA Medical Center, Indianapolis, IN, United States of America
| | - D.M Charytan
- Nephrology Division, NYU School of Medicine and NYU Langone Medical Center, New York, NY, United States of America
| | - T Greene
- Division of Biostatistics, Department of Population Health Sciences, University of Utah, Salt Lake City, UT, United States of America
| | - H.J.L Heerspink
- Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands (The)
| | - A Levin
- Division of Nephrology, University of British Columbia, Vancouver, BC, Canada
| | - B Neal
- The George Institute for Global Health, UNSW Sydney, Sydney, Australia
| | - C Pollock
- Kolling Institute of Medical Research, Sydney Medical School, University of Sydney, Royal North Shore Hospital, St Leonards, NSW, Australia
| | - Y Yavin
- Janssen Research & Development, LLC, Raritan, NJ, United States of America
| | - M Jardine
- The George Institute for Global Health, UNSW Sydney, Sydney, Australia
| | - V Perkovic
- The George Institute for Global Health, UNSW Sydney, Sydney, Australia
| | - C.P Cannon
- Cardiovasular Division, Brigham & Women's Hospital and Baim Institute for Clinical Research, Boston, MA, United States of America
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